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Diversity

Diversity in data sampling is crucial across various use cases, including search, recommendation systems, and more. Ensuring diverse samples means capturing a wide range of variations and perspectives, which leads to more robust, unbiased, and comprehensive models. In search use cases, for instance, diversity helps avoid redundancy, ensuring that users are exposed to a broader set of relevant information rather than repeated similar results.

Papers

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Showing 6526–6550 of 9051 papers

TitleStatusHype
Learning to Identify Ambiguous and Misleading News Headlines—0
Learning to Model Multimodal Semantic Alignment for Story Visualization—0
Learning to Predict Diverse Human Motions from a Single Image via Mixture Density Networks—0
Learning to Sample: an Active Learning Framework—0
Learning to Synthesize Fashion Textures—0
Learning to Walk Autonomously via Reset-Free Quality-Diversity—0
Learning Trajectories are Generalization Indicators—0
Learning Unseen Concepts via Hierarchical Decomposition and Composition—0
Learning utterance-level representations through token-level acoustic latents prediction for Expressive Speech Synthesis—0
Learning Video Representations without Natural Videos—0
Learning Vision-based Pursuit-Evasion Robot Policies—0
Learning Visuo-Haptic Skewering Strategies for Robot-Assisted Feeding—0
Learning What Matters: Probabilistic Task Selection via Mutual Information for Model Finetuning—0
Learning what matters - Sampling interesting patterns—0
Learning with Diversity: Self-Expanded Equalization for Better Generalized Deep Metric Learning—0
LeCoPCR: Legal Concept-guided Prior Case Retrieval for European Court of Human Rights cases—0
LED: Latent Variable-based Estimation of Density—0
Lesion-Aware Transformers for Diabetic Retinopathy Grading—0
Less data is more: Selecting informative and diverse subsets with balancing constraints—0
Less is More: Efficient Point Cloud Reconstruction via Multi-Head Decoders—0
Less Is More: Picking Informative Frames for Video Captioning—0
Lessons to learn for better safeguarding of genetic resources during tree pandemics: the case of ash dieback in Europe—0
Let Me Teach You: Pedagogical Foundations of Feedback for Language Models—0
LetsTalk: Latent Diffusion Transformer for Talking Video Synthesis—0
Leveraging Active Subspaces to Capture Epistemic Model Uncertainty in Deep Generative Models for Molecular Design—0
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